def test_to_svg():
instance = gshhg.GSHHG(get_dirname(), resolution="crude")
figure = get_figure_path("crude.svg")
if figure.exists():
figure.unlink()
assert not figure.exists()
instance.to_svg(figure)
assert figure.exists()
def test_construct():
instance = gshhg.GSHHG(get_dirname(), resolution="crude")
assert instance.polygons() != 0
assert instance.points() != 0
instance = gshhg.GSHHG(get_dirname(),
resolution="crude",
levels=[6],
bbox=(-10, -20, 10, 20))
assert instance.dirname == get_dirname()
assert instance.resolution == "crude"
assert instance.levels == [6]
assert instance.bbox == (-10, -20, 10, 20)
other = pickle.loads(pickle.dumps(instance))
assert other.polygons() == instance.polygons()
assert other.points() == instance.points()
with pytest.raises(FileNotFoundError):
gshhg.GSHHG(get_dirname().parent, resolution="crude")
with pytest.raises(ValueError):
gshhg.GSHHG(get_dirname(), resolution="CRUDE")
with pytest.raises(ValueError):
gshhg.GSHHG(get_dirname(), levels=[0])
with pytest.raises(ValueError):
gshhg.GSHHG(get_dirname(), levels=[7])
with pytest.raises(IndexError):
gshhg.GSHHG(get_dirname(), bbox=(0, ))
def test_nearest():
instance = gshhg.GSHHG(get_dirname(), resolution="crude")
lon1 = np.random.uniform(-180.0, 180.0, 1000)
lat1 = np.random.uniform(-90.0, 90.0, 1000)
lon2, lat2 = instance.nearest(lon1, lat1, num_threads=0)
lon3, lat3 = instance.nearest(lon1, lat1, num_threads=1)
assert np.any(lon1 != lon2)
assert np.any(lat1 != lat2)
assert np.all(lon2 == lon3)
assert np.all(lat2 == lat3)
def test_mask():
instance = gshhg.GSHHG(get_dirname(), resolution="crude")
lon = np.arange(-180, 180, 1, dtype=np.float64)
lat = np.arange(-90, 90, 1, dtype=np.float64)
mx, my = np.meshgrid(lon, lat)
mask1 = instance.mask(mx.flatten(), my.flatten(), num_threads=0)
mask2 = instance.mask(mx.flatten(), my.flatten(), num_threads=1)
assert np.all(mask1 == mask2)
assert set(mask1) == set((0, 1, 2, 3, 5, 6))
def test_grid_mapping_distance_to_nearest():
instance = gshhg.GSHHG(get_dirname(), resolution="crude")
ds = instance.grid_mapping_distance_to_nearest(0.25)
array = ds.distance.data.compute()
assert array.mean() != 0
if HAVE_PLT:
figure = matplotlib.pyplot.figure(figsize=(15, 15), dpi=150)
axe = figure.add_subplot(2, 1, 1)
mx, my = np.meshgrid(ds.lon, ds.lat)
axe.pcolormesh(mx, my, ds.distance, shading='auto')
figure.savefig(get_figure_path("distance_to_nearest.png"),
bbox_inches='tight',
pad_inches=0.4)
def test_grid_mapping_mask():
instance = gshhg.GSHHG(get_dirname(), resolution="crude")
ds = instance.grid_mapping_mask(0.25)
array = ds.mask.data.compute()
assert set(array.flatten()) == set((0, 1, 2, 3, 5, 6))
if HAVE_PLT:
figure = matplotlib.pyplot.figure(figsize=(15, 15), dpi=150)
axe = figure.add_subplot(2, 1, 1)
mx, my = np.meshgrid(ds.lon, ds.lat)
axe.pcolormesh(mx, my, ds.mask, shading='auto')
figure.savefig(get_figure_path("mask.png"),
bbox_inches='tight',
pad_inches=0.4)
def test_distance_to_nearest():
instance = gshhg.GSHHG(get_dirname(), resolution="crude")
lon = np.random.uniform(-180.0, 180.0, 1000)
lat = np.random.uniform(-90.0, 90.0, 1000)
d1 = instance.distance_to_nearest(lon, lat, num_threads=0)
d2 = instance.distance_to_nearest(lon, lat, num_threads=1)
assert np.all(d1 == d2)
d1 = instance.distance_to_nearest(lon, lat, strategy="andoyer")
d2 = instance.distance_to_nearest(lon, lat, strategy="haversine")
d3 = instance.distance_to_nearest(lon, lat, strategy="thomas")
d4 = instance.distance_to_nearest(lon, lat, strategy="vincenty")
assert np.all(d1 != d2)
assert np.all(d1 != d3)
assert np.all(d1 != d4)
assert np.all(d2 != d3)
assert np.all(d2 != d4)
assert np.all(d3 != d4)